RESUMEN
The number of accidents involving elderly individuals has been increasing with the increase of the aging population, posing increasingly serious challenges. Most accidents are caused by reduced judgment and physical abilities, which lead to severe consequences. Therefore, studies on support systems for elderly and visually impaired people to improve the safety and quality of daily life are attracting considerable attention. In this study, a road surface condition distinction method using reflection intensities obtained by an ultrasonic sensor was proposed. The proposed method was applied to movement support systems for elderly and visually impaired individuals to detect dangerous road surfaces and give an alarm. The method did not perform well in previous studies of puddle detection, because the alert provided by the method did not enable users to avoid puddles. This study extended the method proposed by previous studies with respect to puddle detection ability. The findings indicate the effectiveness of the proposed method by considering four road surface conditions. The proposed method could detect puddle conditions. The effectiveness of the proposed method was verified in all four conditions, since users could differentiate between road surface conditions and classify the conditions as either safe or dangerous.
RESUMEN
Absorption, scattering, and color distortion are three major degradation factors in underwater optical imaging. Light rays are absorbed while passing through water, and absorption rates depend on the wavelength of the light. Scattering is caused by large suspended particles, which are always observed in an underwater environment. Color distortion occurs because the attenuation ratio is inversely proportional to the wavelength of light when light passes through a unit length in water. Consequently, underwater images are dark, low contrast, and dominated by a bluish tone. In this paper, we propose a novel underwater imaging model that compensates for the attenuation discrepancy along the propagation path. In addition, we develop a robust color lines-based ambient light estimator and a locally adaptive filtering algorithm for enhancing underwater images in shallow oceans. Furthermore, we propose a spectral characteristic-based color correction algorithm to recover the distorted color. The enhanced images have a reasonable noise level after the illumination compensation in the dark regions, and demonstrate an improved global contrast by which the finest details and edges are enhanced significantly.